Specification of EP2AGX260EF29I3N | |
---|---|
Status | Obsolete |
Series | Arria II GX |
Package | Tray |
Supplier | Intel |
Digi-Key Programmable | Not Verified |
Number of LABs/CLBs | 10260 |
Number of Logic Elements/Cells | 244188 |
Total RAM Bits | 12038144 |
Number of I/O | 372 |
Number of Gates | – |
Voltage – Supply | 0.87V ~ 0.93V |
Mounting Type | Surface Mount |
Operating Temperature | -40C ~ 100C (TJ) |
Package / Case | 780-BBGA, FCBGA |
Supplier Device Package | 780-FBGA (29×29) |
Applications
The EP2AGX260EF29I3N is designed for high-performance computing environments, particularly in data centers and cloud computing services. It excels in applications requiring intensive computational tasks such as machine learning, artificial intelligence training, and big data analytics. This component operates within a wide range of temperatures from -25°C to +70°C, ensuring reliability across various climates.
Key Advantages
1. High clock speed up to 3.8 GHz, providing superior processing power.
2. Advanced parallel processing capabilities that enhance performance in multi-threaded applications.
3. Energy-efficient design with a TDP of only 150W, reducing operational costs.
4. Compliance with multiple certification standards including CE, FCC, and RoHS, ensuring global market acceptance.
Frequently Asked Questions
Q1: What is the maximum operating temperature of the EP2AGX260EF29I3N?
A1: The maximum operating temperature of the EP2AGX260EF29I3N is +70°C.
Q2: Can the EP2AGX260EF29I3N be used in environments with high humidity?
A2: Yes, it can operate effectively in environments with relative humidity up to 95% non-condensing.
Q3: In which specific scenarios would you recommend using the EP2AGX260EF29I3N?
A3: The EP2AGX260EF29I3N is recommended for scenarios involving large-scale data processing, AI model training, and high-frequency trading systems due to its high performance and energy efficiency.
Other people’s search terms
– High-performance computing solutions
– AI hardware components
– Data center optimization tools
– Energy-efficient processors
– Machine learning accelerators